Papers by Roman Garaev
Efficient Hallucination Detection in Automatic Code Generation (2026.findings-acl)
Copied to clipboard
| Challenge: | Large language models produce source code that appears correct and well-formed, but includes hallucinated elements that cause downstream test failures. |
| Approach: | They develop a transformer-based detector that uses LLM internal representations to identify hallucinations. |
| Outcome: | The proposed detector outperforms existing methods and unsupervised methods in the code generation domain. |